Advances in Differential Privacy and Differentially Private Machine Learning

arXiv:2404.04706v1 Announce Type: new
Abstract: There has been an explosion of research on differential privacy (DP) and its various applications in recent years, ranging from novel variants and accounting techniques in differential privacy to the thriving field of differentially private machine learning (DPML) to newer implementations in practice, like those by various companies and organisations such as census bureaus. Most recent surveys focus on the applications of differential privacy in particular contexts like data publishing, specific machine learning tasks, analysis …

accounting applications arxiv cs.cr differential privacy explosion machine machine learning novel practice privacy private research techniques